Deep Learning for Automatic Cell Detection in Wide-Field Microscopy Zebrafish Images

Dong, Bo, Shao, Ling, da Costa, Marc, Bandmann, Oliver and Frangi, Alejandro F. (2015) Deep Learning for Automatic Cell Detection in Wide-Field Microscopy Zebrafish Images. In: ISBI '15: International Symposium on Biomedical Imaging, 16th - 19th April 2015, New York, US.

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Official URL: http://dx.doi.org/10.1109/ISBI.2015.7163986

Abstract

The zebrafish has become a popular experimental model organism for biomedical research. In this paper, a unique framework is proposed for automatically detecting Tyrosine Hydroxylase-containing (TH-labeled) cells in larval zebrafish brain z-stack images recorded through the wide-field microscope. In this framework, a supervised max-pooling Convolutional Neural Network (CNN) is trained to detect cell pixels in regions that are preselected by a Support Vector Machine (SVM) classifier. The results show that the proposed deep-learned method outperforms hand-crafted techniques and demonstrate its potential for automatic cell detection in wide-field microscopy z-stack zebrafish images.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Machine learning, Microscopy - Light, Single cell & molecule detection
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:
Depositing User: Paul Burns
Date Deposited: 16 Jun 2015 08:26
Last Modified: 27 Oct 2015 10:54
URI: http://nrl.northumbria.ac.uk/id/eprint/22922

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